Jottings …

L ess is more. At least when it comes to diagnosis, where simplifying a tool can make it more readily usable at the bedside. In this issue are several short or shortened tools for diagnosis and prognosis. Shorter tools are not just timesaving: they can be as accurate or more accurate for 2 reasons. First, adding weak diagnostic information to good information can degrade the overall performance: as we add items to a clinical prediction rule accuracy initially improves but then begins to get worse as we add weaker information. The poor information pollutes the good. Statisticians call this "overfitting" of a model. Second, a more complex model may be less robust when transferred to new settings. If during a 10-minute general practice consultation the possibility of dementia occurs to me, doing a Mini-Mental State (MMS) exam is usually not feasible. So I use an alternative 2-minute test— the MiniCog (the combination of a 3-item recall plus a clock-face drawing), which we have abstracted in a previous issue. But if you are considering a full MMS, it will be easier to begin with the short version described in this issue. Similarly, we have previously described a tool for diagnosing anxiety: the GAD-7, a 7-item questionnaire. Well, this can be further shortened down to just 2 questions: ‘‘over the last 2 weeks how often have you been bothered by (i) feeling nervous, anxious, or on edge, and (ii) not being able to stop or control worrying? Coeliac disease often goes undetected, particularly in older patients with milder forms of the disease. So being alert for the possibility and having a simple approach to testing is worthwhile. Hopper categorised patients with weight loss, anaemia, or diarrhoea as having a "high risk" of coeliac disease, and added to this the tissue transglutaminase. Around a third of high risk patients with a positive tissue transglutaminase anitbody test had coeliac disease, whereas if both were negative none (of 1170 patients) had it. Prognostic tools may also benefit from shortening. The first in this issue is a 9-question tool for predicting which patients with undifferentiated arthritis are most likely to develop rheumatoid arthritis. Given the benefits of early diseasemodifying anti-rheumatic drugs, it would be worth following such patients more closely.

L ess is more. At least when it comes to diagnosis, where simplifying a tool can make it more readily usable at the bedside. In this issue are several short or shortened tools for diagnosis and prognosis. Shorter tools are not just timesaving: they can be as accurate or more accurate for 2 reasons. First, adding weak diagnostic information to good information can degrade the overall performance: as we add items to a clinical prediction rule accuracy initially improves but then begins to get worse as we add weaker information. The poor information pollutes the good. Statisticians call this "overfitting" of a model. Second, a more complex model may be less robust when transferred to new settings.
If during a 10-minute general practice consultation the possibility of dementia occurs to me, doing a Mini-Mental State (MMS) exam is usually not feasible. So I use an alternative 2-minute test-the MiniCog (the combination of a 3-item recall plus a clock-face drawing), which we have abstracted in a previous issue. But if you are considering a full MMS, it will be easier to begin with the short version described in this issue. Similarly, we have previously described a tool for diagnosing anxiety: the GAD-7, a 7-item questionnaire. Well, this can be further shortened down to just 2 questions: ''over the last 2 weeks how often have you been bothered by (i) feeling nervous, anxious, or on edge, and (ii) not being able to stop or control worrying?
Coeliac disease often goes undetected, particularly in older patients with milder forms of the disease. So being alert for the possibility and having a simple approach to testing is worthwhile. Hopper categorised patients with weight loss, anaemia, or diarrhoea as having a "high risk" of coeliac disease, and added to this the tissue transglutaminase. Around a third of high risk patients with a positive tissue transglutaminase anitbody test had coeliac disease, whereas if both were negative none (of 1170 patients) had it. Prognostic tools may also benefit from shortening. The first in this issue is a 9-question tool for predicting which patients with undifferentiated arthritis are most likely to develop rheumatoid arthritis. Given the benefits of early diseasemodifying anti-rheumatic drugs, it would be worth following such patients more closely.

INTRODUCTION
Evidence-based medicine (EBM) has been defined as the ''integration of best research evidence with clinical expertise and patient values.'' 1 Though a laudable ideal, it is not feasible for individual clinicians to review, interpret, and apply all relevant evidence all the time. Hence clinicians should have access to ''a set of tools and resources for finding and applying current best evidence from research for the care of individual patients.'' 2 The goal of clinical guideline writers is to perform part of this role, but they too must resolve these practical challenges if they are to provide tools to help clinicians deliver real evidence-based practice. 3-4 Here we consider some challenges for guideline writers when producing clinical advice that meets the demands of busy clinicians.

INTERPRETATION AND APPLICATION OF EVIDENCE
Knowledge to support decision making may be derived from published research, locally generated data, clinician experience, the law, and patient perspectives. Each can be regarded as ''supporting evidence,'' so sometimes confusion arises in discussions about evidence and EBM. For treatment evaluation, quantitative research evidence (in particular from randomised clinical trials [RCTs] and systematic reviews of RCTs) generally has primary importance over other forms of evidence. 5 But evidence from well conducted studies alone rarely provides answers to all questions in a particular clinical situation. Hence giving best advice requires us to extrapolate and integrate the evidence to meet the demands of everyday clinical practice. This process requires interpretation and judgment.
To be of value to a clinician, trials must be up-to-date and valid, and have used clinically relevant doses, patients, comparators, end points, and durations. 6 Interpreters of these trials must reconcile conflicting results and take into account publication bias, reviewer bias, and relevance to current practice. 7-9 They must check that clinically important details are not hidden, overlooked, or ''averaged out'' by the methods of the study. 10 The averaging-out implicit in statistical analysis diminishes the applicability to any one individual and oversimplifies the choices to be made. Showing that one treatment is better than another on average does not mean it is the best treatment for every individual. 10 Interpreters must also reconcile the mismatch between the narrowly defined group of patients in a trial and the patients in the clinical environment, and they must consider local issues such as costs, services, and laws and cultures. In individual cases a therapy may not be appropriate because of coexisting diseases, contraindicated comedications, risk factors, health status, patient preferences, or patient circumstances.